Has apreferred AIresearch toolthey canrecommendIs optimisticabout thefuture ofhuman-AIcollaborationKnows atleast threeprogramminglanguagesCan namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHascontributedto an open-source AIprojectHas learneda newlanguage inthe last yearHas traveledinternationallyto attend thisconferenceCan explain thedifferencebetween causaland maskedlanguagemodelsHasattended anICMLconferencebeforeHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersCanrecommenda good AI ortech relatedpodcastHas experiencewith low-resourcelanguages inNLPHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationHas used agenerative AImodel for anon-academicpurposeHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHasexperiencewith fine-tuning a pre-trained LLMHaspublishedresearch onmultilingualLLMsHas collaboratedon a researchpaper withsomeone from adifferent continentIs familiarwith theconcept ofpromptengineeringHas apreferred AIresearch toolthey canrecommendIs optimisticabout thefuture ofhuman-AIcollaborationKnows atleast threeprogramminglanguagesCan namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHascontributedto an open-source AIprojectHas learneda newlanguage inthe last yearHas traveledinternationallyto attend thisconferenceCan explain thedifferencebetween causaland maskedlanguagemodelsHasattended anICMLconferencebeforeHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersCanrecommenda good AI ortech relatedpodcastHas experiencewith low-resourcelanguages inNLPHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationHas used agenerative AImodel for anon-academicpurposeHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHasexperiencewith fine-tuning a pre-trained LLMHaspublishedresearch onmultilingualLLMsHas collaboratedon a researchpaper withsomeone from adifferent continentIs familiarwith theconcept ofpromptengineering

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has a preferred AI research tool they can recommend
  2. Is optimistic about the future of human-AI collaboration
  3. Knows at least three programming languages
  4. Can name three different LLM architectures
  5. Has successfully debugged a complex LLM
  6. Has contributed to an open-source AI project
  7. Has learned a new language in the last year
  8. Has traveled internationally to attend this conference
  9. Can explain the difference between causal and masked language models
  10. Has attended an ICML conference before
  11. Has used a generative AI model to create art or music
  12. Is currently working on a project involving cross-lingual transfer learning
  13. Has used an LLM to summarize research papers
  14. Can recommend a good AI or tech related podcast
  15. Has experience with low-resource languages in NLP
  16. Has participated in a hackathon focused on AI or LLMs
  17. Is excited about the potential of LLMs in education
  18. Has used a generative AI model for a non-academic purpose
  19. Has presented a paper on natural language generation
  20. Is interested in the ethical implications of generative AI
  21. Has experience with fine-tuning a pre-trained LLM
  22. Has published research on multilingual LLMs
  23. Has collaborated on a research paper with someone from a different continent
  24. Is familiar with the concept of prompt engineering